Update model card for yolov8-det

README.md

@@ -211,6 +211,12 @@ Row conventions in the table below:
 | Medium | NXP Ara240 (FRDM) — throughput | 59.99% | -4.69 | 42.66% | 21.56 | 34.45 | 54.1 | ~54 | [v-a2f](https://edgefirst.studio/public/validation/v-a2f/details?mode=charts) |
 | Medium | Raspberry Pi 5 + Hailo-8L NPU | 63.88% | -0.80 | 47.67% | 56.26 | 71.51 | 16.9 | ~17 | [v-90a](https://edgefirst.studio/public/validation/v-90a/details?mode=charts) |
 | Medium | NVIDIA Jetson Orin Nano (TensorRT FP16) | 64.67% | -0.01 | 48.41% | 52.44 | 64.24 | 75.3 | ~75 | [v-92b](https://edgefirst.studio/public/validation/v-92b/details?mode=charts) |
+|  | Apple iPhone 17 Pro — CoreML Neural Engine (FP16) | 63.82% | -0.86 | 47.68% | 14.26 | 19.28 | 132.6 | ~70 | [v-f5a](https://edgefirst.studio/public/validation/v-f5a/details?mode=charts) |
+|  | Apple iPhone 17 Pro — CoreML Metal GPU (FP16) | 63.81% | -0.87 | 47.69% | 37.08 | 46.29 | 51.8 | ~27 | [v-f58](https://edgefirst.studio/public/validation/v-f58/details?mode=charts) |
+|  | Apple iPhone 17 Pro — CoreML CPU (FP16) | 63.85% | -0.83 | 47.67% | 107.09 | 113.74 | 18.5 | ~9 | [v-f40](https://edgefirst.studio/public/validation/v-f40/details?mode=charts) |
+|  | Apple iPhone 15 Pro — CoreML Neural Engine (FP16) | 63.82% | -0.86 | 47.69% | 21.73 | 27.54 | 87.6 | ~46 | [v-f1d](https://edgefirst.studio/public/validation/v-f1d/details?mode=charts) |
+|  | Apple iPhone 15 Pro — CoreML Metal GPU (FP16) | 63.82% | -0.86 | 47.69% | 133.87 | 149.08 | 14.5 | ~7 | [v-f2a](https://edgefirst.studio/public/validation/v-f2a/details?mode=charts) |
+|  | Apple iPhone 15 Pro — CoreML CPU (FP16) | 63.84% | -0.84 | 47.66% | 142.21 | 151.93 | 13.9 | ~7 | [v-f2d](https://edgefirst.studio/public/validation/v-f2d/details?mode=charts) |